AI Layoffs are a Short-Term Bet
The news is full of alarm around companies, even major ones like Spotify are letting their software engineers go because parts of their work can now be replaced by AI. Many companies show this trend, but we think it's temporary.
Right now, product-oriented companies like Spotify, built around a single core product, can afford to do this and likely don't yet know the long-term repercussions. Layoffs may improve a quarterly earnings report, but that's just because you vastly reduced your expenses on salaries (though, Spotify is already starting to feel the repercussions). Despite the aggressive adoption of AI in their workflow, open Spotify today and tell me it has every feature you ever wanted, or that it's perfectly bug free, or that nothing there annoys you.
Execution vs Judgement
AI is great at accomplishing assigned tasks. Fix this bug. Refactor this function. Investigate issue X. It will happily do so. What it is not great at is judgment.
Why Judgement Matters
This issue expands into code quality and security. An AI will happily "find" a flaw if prompted to look for one. This is especially evident in the recent benchmark that demonstrates that even the smarted AI models can easily miss critical security vulnerabilities, or make ones up where they don't exist. It demonstrates how models optimize for satisfying the prompt, not for validating whether the premise itself is sound.
It is not great at mulling through thousands of bug reports and distinguishing between "this is a legitimate bug or usability issue" and "this is a user misunderstanding something that works as intended" You yourself have probably criticized a feature only to later realize you were using it wrong. That is not a bug, it is a UX issue.
UX is a deeply human problem. It requires empathy and insight into how people actually use software, not just how it was designed to be used. That context is rarely fully captured in text , which is what AI trains on. If you give an an AI a bug statement like "User found issue X, investigate and fix it," it will investigate and fix it. Even if the best solution was not a code change,but a clearer onboarding or more guidance on using the product.
AI is an Extension of Engineers
Even if you manage to reduce that behavior, you are still left with the fundamental truth: AI is fueled by human creativity and corrected by expertise. Across Rust, Python,Java, Kotlin, TypeScript, and more, AI can generate impressive code. But long-term, product-level, maintainable systems still require oversight and strict architectural constraints with someone defining those constraints.
AI replaces boilerplate and repetitive coding. It is an extension of an engineer, not a replacement. You can choose to make it an extension of a few senior engineers while replacing juniors. Or you can promote your juniors, equip your team with AI, and build more products, faster than ever before.
Is it optimization or Growth?
Spotify & similar companies can get away with layoffs because they operate primarily on a single product & are focused on ways to optimize their workflow & operations. But optimization is not the same as expansion. A product polished to perfection but slow to evolve risks becoming irrelevant. Evernote for example was seamless and performant. It was also overtaken by products that moved faster & stayed more relevant.
This is less about whether AI replaces engineers and more about how companies choose to use it. Shrink headcount & polish what exists, or amplify your team and accelerate what comes next.
Knowing how to use AI
Often the real issue is not AI capability but the skill required to use it well. Developing effectively with AI does not come naturally. It requires structured documentation, disciplined prompting, critical validation of outputs, and architectural awareness. That barrier can make it seem easier to replace engineers than to empower them. But it is a skill & skills can be learned.
Over time engineers will learn it. When they do, companies may realize the missed opportunity was not in reducing payroll, but in failing to compound their creative capacity.
Helping Engineers get there
At NetFire, we teach engineers how to understand AI at a deeper level and integrate it properly into their workflows. Not another short-lived prompt engineering course, but a way to scale their work and stay ahead of the industry. [Get in touch](https://netfire.com/#homepage-cta) and help your engineers excel using AI.
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